How to connect Google Cloud BigQuery and Scrapeless
Create a New Scenario to Connect Google Cloud BigQuery and Scrapeless
In the workspace, click the “Create New Scenario” button.

Add the First Step
Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Google Cloud BigQuery, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud BigQuery or Scrapeless will be your first step. To do this, click "Choose an app," find Google Cloud BigQuery or Scrapeless, and select the appropriate trigger to start the scenario.

Add the Google Cloud BigQuery Node
Select the Google Cloud BigQuery node from the app selection panel on the right.

Google Cloud BigQuery
Configure the Google Cloud BigQuery
Click on the Google Cloud BigQuery node to configure it. You can modify the Google Cloud BigQuery URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Scrapeless Node
Next, click the plus (+) icon on the Google Cloud BigQuery node, select Scrapeless from the list of available apps, and choose the action you need from the list of nodes within Scrapeless.

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Authenticate Scrapeless
Now, click the Scrapeless node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Scrapeless settings. Authentication allows you to use Scrapeless through Latenode.
Configure the Google Cloud BigQuery and Scrapeless Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the Google Cloud BigQuery and Scrapeless Integration
Use various Latenode nodes to transform data and enhance your integration:
- Branching: Create multiple branches within the scenario to handle complex logic.
- Merging: Combine different node branches into one, passing data through it.
- Plug n Play Nodes: Use nodes that don’t require account credentials.
- Ask AI: Use the GPT-powered option to add AI capabilities to any node.
- Wait: Set waiting times, either for intervals or until specific dates.
- Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
- Iteration: Process arrays of data when needed.
- Code: Write custom code or ask our AI assistant to do it for you.

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AI Anthropic Claude 3
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Scrapeless
Trigger on Webhook
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Save and Activate the Scenario
After configuring Google Cloud BigQuery, Scrapeless, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.
Test the Scenario
Run the scenario by clicking “Run once” and triggering an event to check if the Google Cloud BigQuery and Scrapeless integration works as expected. Depending on your setup, data should flow between Google Cloud BigQuery and Scrapeless (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Google Cloud BigQuery and Scrapeless
Scrapeless + Google Sheets + Slack: Scrape product data from a website using Scrapeless, add the data as a new row in Google Sheets, and then send a Slack message notifying the team about the updated product information.
Google Sheets + Scrapeless + Slack: Triggered when a new row is added to a Google Sheet, this flow uses Scrapeless to search Google for related news articles based on the data in the row. A summary of the news is then sent to a Slack channel.
Google Cloud BigQuery and Scrapeless integration alternatives
About Google Cloud BigQuery
Use Google Cloud BigQuery in Latenode to automate data warehousing tasks. Query, analyze, and transform huge datasets as part of your workflows. Schedule data imports, trigger reports, or feed insights into other apps. Automate complex analysis without code and scale your insights with Latenode’s flexible, pay-as-you-go platform.
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About Scrapeless
Use Scrapeless in Latenode to extract structured data from websites without code. Scrape product details, news, or social media feeds, then pipe the data into your Latenode workflows. Automate lead generation, price monitoring, and content aggregation. Combine Scrapeless with Latenode's AI nodes for smarter data processing.
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See how Latenode works
FAQ Google Cloud BigQuery and Scrapeless
How can I connect my Google Cloud BigQuery account to Scrapeless using Latenode?
To connect your Google Cloud BigQuery account to Scrapeless on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud BigQuery and click on "Connect".
- Authenticate your Google Cloud BigQuery and Scrapeless accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automate web data scraping and analysis using Google Cloud BigQuery and Scrapeless integration?
Yes, easily! Latenode automates data flow, allowing you to scrape data with Scrapeless and store it in Google Cloud BigQuery for analysis, without code. Get insights faster!
What types of tasks can I perform by integrating Google Cloud BigQuery with Scrapeless?
Integrating Google Cloud BigQuery with Scrapeless allows you to perform various tasks, including:
- Automatically backing up scraped website data to Google Cloud BigQuery.
- Analyzing web data trends from Scrapeless in Google Cloud BigQuery.
- Creating real-time dashboards from scraped and analyzed data.
- Building custom reports with integrated data from both platforms.
- Enriching existing Google Cloud BigQuery data with fresh web data.
How secure is the Google Cloud BigQuery integration within the Latenode platform?
Latenode employs industry-standard security practices, including encryption, to ensure the secure transfer and storage of data between Google Cloud BigQuery and Scrapeless.
Are there any limitations to the Google Cloud BigQuery and Scrapeless integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large datasets might require optimized queries to ensure efficient processing.
- Rate limits on Scrapeless can impact the speed of data extraction.
- Complex data transformations may require JavaScript knowledge.